In this talk I will present preliminary research results that I presented at the IEEE International Conference on Semantic Computing in Berkeley, CA. We show how natural language queries can be
represented as subnetworks within ontologies in order to extract implicit semantics from the input. Interesting features of the approach include: methods for modeling spatial and temporal concepts and their linguistic realizations, reliance on shallow surface features, and integration of techniques based in the semantic web, database, and natural language processing communities. The initial proof-of-concept implementation and evaluation shows the approach is promising for generating useful semantic representations of queries for the purpose of generating formal database queries.

Biography:

Joel Booth is a Ph.D. an CTS IGERT Fellow and student in the Department of Computer Science at University of Illinois at Chicago. His research interests lie between multiple interrelated fields:
natural language processing, semantic web, and databases. His dissertation research focuses on developing database models for transportation systems as well as natural language interfaces that
facilitate their access by lay-users. He completed his B.A. in Computer Science at Kalamazoo College in 2005, and joined UIC in the fall of 2005.